---
title: Kausalyze Featured in Chemical Engineering Magazine
description: Root-cause analysis investigations can be streamlined with artificial intelligence (AI), but only if it can be explained by human engineers.
image: https://www.kausalyze.com/hubfs/Chemical-Engineering-2026-HubSpot-2x1-2400x1200-v3%20crop.jpg
---

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# Kausalyze Featured in Chemical Engineering Magazine

By Kausalyze11 August 2026

![Chemical Engineering Magazine](https://www.kausalyze.com/hubfs/Chemical-Engineering-2026-HubSpot-2x1-2400x1200-v3%20crop.jpg)

From the journal

Causal AI, process engineering and industrial progress.

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We are delighted to see Kausalyze featured in *Chemical Engineering*, one of the most respected industry publications serving the global chemical and process industries.

The article, **“[Why Process Industries Need Causal AI, Not Just Predictive Maintenance](https://www.chemengonline.com/why-process-industries-need-causal-ai-not-just-predictive-maintenance/),”** was written by Kausalyze Founder and CEO Dr Louis Allen. It explores one of the most significant challenges facing process manufacturers: how to turn the vast amount of operational data already being collected into trusted intelligence that helps engineers make faster, better-informed decisions.

The article showcases how artificial intelligence can create genuine value in complex industrial environments and examines why conventional predictive tools often stop short of answering the question engineers most need resolved: why is this happening, and what should we do about it?

As the article explains:

“Prediction may tell you something could go wrong. Causal understanding is what helps you stop it.”

This distinction lies at the heart of Kausalyze. Our explainable causal AI technology is designed to help engineering teams move beyond correlations and alerts to understand the cause and effect relationships behind process problems. By presenting transparent evidence that engineers can review, challenge and validate, the technology supports – not replaces – engineering judgement.

The feature also highlights the potential for causal AI to accelerate root-cause investigations, preserve valuable operational knowledge and help manufacturers improve reliability, efficiency and production performance.

We are proud to see the thinking behind Kausalyze recognised and shared through such an important industry platform.

**Read the full article:**   
*Why Process Industries Need Causal AI, Not Just Predictive Maintenance*   
By Dr Louis Allen, Founder and CEO, Kausalyze   
Published by *Chemical Engineering*, 29 June 2026   
[https://www.chemengonline.com/why-process-industries-need-causal-ai-not-just-predictive-maintenance/](https://www.chemengonline.com/why-process-industries-need-causal-ai-not-just-predictive-maintenance/)

## Join the discussion

Share a question or perspective on this article.

## Bring the question back to your plant.

Explore how a causal model could help investigate a recurring problem and determine what to change.

[Book a technical review](https://www.kausalyze.com/book-demo)

[![Kausalyze](https://www.kausalyze.com/hubfs/raw_assets/public/kausalyze-rebuild/logo.svg)](https://www.kausalyze.com/)

Causal AI for process manufacturing. A University of Sheffield spinout, founded by chemical engineers.

#### Product

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#### Company

- [About](https://www.kausalyze.com/about)
- [Contact](https://www.kausalyze.com/contact)
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#### Resources

- [Insights](https://www.kausalyze.com/kausalyze-ltd-blog/tag/insights)
- [News](https://www.kausalyze.com/kausalyze-ltd-blog/tag/news)

© 2026 Kausalyze Ltd. Sheffield, United Kingdom. [Privacy](https://www.kausalyze.com/privacy)

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